Red blood cells (RBC) stored in approved additive solutions undergo a set of metabolic and physicochemical changes referred to as `storage lesions' reducing the efficacy and safety of older transfused RBC units. Though the consequences of the storage lesion are slowly becoming well documented, a major reason for delayed progress in developing new technologies for quality and safety of RBC transfusion is the lack of global understanding of metabolic decline during storage. There has been interest to utilize high-throughput metabolite profiling for global understanding of RBC metabolic decline but data analysis of complex datasets has been a daunting challenge. In Phase I of this program, we developed the first, robust computational platform involving statistical analysis, systems biology of metabolic networks, and data-driven kinetic models to fully interpret and analyze RBC metabolite-profiles in a complete network context. Using time-course global, quantitative metabolite profiling, we determined that RBCs undergo a clinically relevant non-linear decay process and computationally identified key metabolic enzymes that drive this decay process. Based on the computational results, we have devised two novel additive solution strategies to mitigate the decay process and improve the safety and accuracy of RBC transfusion. In this proposal, we will validate the computationally determined additive solutions for efficacy in alleviating the non-linear decay process through 1) metabolomics experiments, and 2) non-metabolic RBC physiology experiments including cell rheology and microparticle generation. A successful additive solution will be progressed to media refinement and preclinical testing.